R6_par_discretenum | R Documentation |
R6 object for discrete numeric
R6 object for discrete numeric
Parameter with uniform distribution for hyperparameter optimization
comparer::par_hype
-> par_discretenum
name
Name of the parameter, must match the input to 'eval_func'.
values
Values, discrete numeric
ggtrans
Transformation for ggplot, see ggplot2::scale_x_continuous()
fromraw()
Function to convert from raw scale to transformed scale
R6_par_discretenum$fromraw(x)
x
Value of raw scale
toraw()
Function to convert from transformed scale to raw scale
R6_par_discretenum$toraw(x)
x
Value of transformed scale
generate()
Generate values in the raw space based on quantiles.
R6_par_discretenum$generate(q)
q
In [0,1].
getseq()
Get a sequence, uniform on the transformed scale
R6_par_discretenum$getseq(n)
n
Number of points. Ignored for discrete.
isvalid()
Check if input is valid for parameter
R6_par_discretenum$isvalid(x)
x
Parameter value
convert_to_mopar()
Convert this to a parameter for the mixopt R package.
R6_par_discretenum$convert_to_mopar(raw_scale = FALSE)
raw_scale
Should it be on the raw scale?
new()
Create a hyperparameter with uniform distribution
R6_par_discretenum$new(name, values)
name
Name of the parameter, must match the input to 'eval_func'.
values
Numeric values, must be in ascending order
print()
Print details of the object.
R6_par_discretenum$print(...)
...
not used
clone()
The objects of this class are cloneable with this method.
R6_par_discretenum$clone(deep = FALSE)
deep
Whether to make a deep clone.
p1 <- R6_par_discretenum$new('x1', 0:2)
class(p1)
print(p1)
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